Seems I've stumbled onto a beehive. France has set its sights to be the leader 
in the AI arms race, together with deep mind. I'll go look on some old hard 
drives for the links. Interesting times!
________________________________
From: Stefan Reich via AGI <[email protected]>
Sent: Wednesday, 12 September 2018 4:21 PM
To: AGI
Subject: Re: [agi] Growing Knowledge

That sounds interesting, please look it up if you can.

On Wed, 12 Sep 2018 at 15:26, Nanograte Knowledge Technologies via AGI 
<[email protected]<mailto:[email protected]>> wrote:
Jim

Bootstrapping a computational platform with domain knowledge (seeding with 
insights), was already done a few years ago by the ex head of AI research in 
France. I need to find his blogs again, but apparently he had amazing results 
with regards re-solving classical mathematical problems.

Our question is; would that constitute AGI?

I  appreciate your comment on how such an approach would not be considered 
radical at all. However, the claim you make immediately thereafter; that the 
approach would help to think of the problem in a different way, is refutable.

The thinking in terms of relationships suffer the same fate. Not radical, and 
not thinking in a new or different way.

As such, we need to think as radically as we could possibly do. We need to find 
a few radical approaches and see if they could be focused on a few avenues of 
pragmatic research. May the best approach win.

For example, instead of relationships, thinking free-will (random) 
associations. This is not a semantic ploy, but a radical departure in terms of 
AGI architecture.

Furthermore, instead of thinking of seeding, rather allowing the computational 
platform to Find, Frame, Make and Share. This would denote another radical 
departure in current thinking (I did come across a similar approach recently).

Rob




________________________________
From: Jim Bromer via AGI <[email protected]<mailto:[email protected]>>
Sent: Wednesday, 12 September 2018 2:25 PM
To: [email protected]<mailto:[email protected]>
Subject: [agi] Growing Knowledge

The idea that an AGI program has to be able to 'grow' knowledge is not
conceptually radical but the use of the idea that a program might be
seeded with certain kinds of insights does make me think about the
problem in a slightly different way. By developing a program to work
along principles that are meant to incorporate some way to build on
the basis of insights that are provided as the program explores
different kinds of subjects I think I might be able to see this theory
in the terms of a transition from programming discrete instructions
that correspond to a particular sequence of computer operations into
programming with instructions that have a potential to grow
relationships between the knowledge data. The kinds of relationships
do not need to be absolutely pre-determined because the use of basic
relationships and references to specific ideas can implicitly develop
into more sophisticated relationships that would only need to be
recognized. For example, an abstraction of generalization seems pretty
fundamental to Old AI. However, I believe that just by using more
basic relationships which can refer to other specific ideas and to
groups of ideas, the relationships that will effectively refer to a
kind of abstraction may develop naturally - in primitive forms. It
would be necessary to 'teach' the AGI program to recognize and
appreciate these abstractions so that it could then use abstraction
more explicitly.
Jim Bromer


--
Stefan Reich
BotCompany.de // Java-based operating systems
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